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Found 2 papers, 1 papers with code
Does resistance to style-transfer equal Global Shape Bias? Measuring network sensitivity to global shape configuration
The current benchmark for evaluating a model's global shape bias is a set of style-transferred images with the assumption that resistance to the attack of style transfer is related to the development of global structure sensitivity in the model.
Model-Aware Contrastive Learning: Towards Escaping the Dilemmas
Contrastive learning (CL) continuously achieves significant breakthroughs across multiple domains.
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